File size: 8,072 Bytes
082393b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 | """Remote inference via an OpenAI-compatible API endpoint.
Used when MODEL_API_URL and RITS_API_KEY environment variables are set.
Provides drop-in replacements for the local inference functions in
infer_vision_qa and infer_chart2csv.
"""
from __future__ import annotations
import base64
import io
import json
import logging
import os
import traceback
from collections.abc import Generator
from typing import Any
import requests
from PIL import Image
from model_loader import get_model_name
logger = logging.getLogger(__name__)
def _pil_to_data_uri(image: Image.Image) -> str:
"""Convert a PIL Image to a base64 data URI."""
buf = io.BytesIO()
image.save(buf, format="PNG")
b64 = base64.b64encode(buf.getvalue()).decode("utf-8")
return f"data:image/png;base64,{b64}"
def _build_api_url() -> str:
"""Build the chat completions endpoint URL from MODEL_API_URL."""
url = os.environ["MODEL_API_URL"].rstrip("/")
if url.endswith("/chat/completions"):
return url
if url.endswith("/v1"):
return f"{url}/chat/completions"
return f"{url}/v1/chat/completions"
def _translate_messages(conversation: list[dict], image: Image.Image) -> list[dict]:
"""Convert local-format messages to OpenAI vision API format.
Replaces ``{"type": "image"}`` entries with the ``image_url`` structure
expected by the OpenAI vision API.
"""
translated = []
for msg in conversation:
new_content = []
for item in msg["content"]:
if item.get("type") == "image":
new_content.append({
"type": "image_url",
"image_url": {"url": _pil_to_data_uri(image)},
})
else:
new_content.append(item)
translated.append({"role": msg["role"], "content": new_content})
return translated
def _call_chat_api(messages: list[dict]) -> str:
"""Send a chat completion request to the remote API and return the response text."""
url = _build_api_url()
headers = {
"Content-Type": "application/json",
"RITS_API_KEY": os.environ["RITS_API_KEY"],
}
payload = {
"model": get_model_name(),
"messages": messages,
"max_tokens": 4096,
}
resp = requests.post(url, json=payload, headers=headers, timeout=120)
resp.raise_for_status()
return resp.json()["choices"][0]["message"]["content"]
def _call_chat_api_stream(messages: list[dict]) -> Generator[str, None, None]:
"""Send a streaming chat completion request and yield token chunks."""
url = _build_api_url()
model = get_model_name()
headers = {
"Content-Type": "application/json",
"RITS_API_KEY": os.environ["RITS_API_KEY"],
}
payload = {
"model": model,
"messages": messages,
"max_tokens": 4096,
"stream": True,
}
logger.debug("Stream request: POST %s model=%s messages=%d", url, model, len(messages))
for i, msg in enumerate(messages):
content_types = [c.get("type") for c in msg.get("content", [])]
logger.debug(" message[%d] role=%s content_types=%s", i, msg.get("role"), content_types)
try:
resp = requests.post(url, json=payload, headers=headers, timeout=120, stream=True)
logger.debug("Stream response: status=%d headers=%s", resp.status_code, dict(resp.headers))
resp.raise_for_status()
except requests.RequestException:
logger.exception("Stream request failed: POST %s", url)
raise
for line in resp.iter_lines(decode_unicode=True):
if not line or not line.startswith("data:"):
continue
data = line[len("data:"):].strip()
if data == "[DONE]":
logger.debug("Stream complete: received [DONE]")
break
try:
chunk = json.loads(data)
if "error" in chunk:
err_msg = chunk["error"].get("message", "Unknown server error")
err_code = chunk["error"].get("code", "unknown")
logger.error("Server error in stream: code=%s message=%s full_error=%s", err_code, err_msg, chunk["error"])
yield f"Error: Remote API returned {err_code} — {err_msg}"
return
content = chunk["choices"][0]["delta"].get("content", "")
if content:
yield content
except (json.JSONDecodeError, KeyError, IndexError):
logger.warning("Failed to parse stream chunk: %s", data[:200])
continue
def answer_question_api(
image: Image.Image,
question: str,
conversation_history: list[dict[str, Any]],
current_image_path: str | None,
) -> tuple[str, list[dict[str, Any]], str | None]:
"""Answer a question about an image via the remote API.
Drop-in replacement for ``infer_vision_qa.answer_question``.
"""
try:
image = image.convert("RGB")
if not conversation_history:
new_user_turn: dict[str, Any] = {"role": "user", "content": [
{"type": "image"},
{"type": "text", "text": question},
]}
else:
new_user_turn = {"role": "user", "content": [
{"type": "text", "text": question},
]}
conversation = [*conversation_history, new_user_turn]
api_messages = _translate_messages(conversation, image)
answer = _call_chat_api(api_messages)
updated_history = [
*conversation_history,
new_user_turn,
{"role": "assistant", "content": [{"type": "text", "text": answer}]},
]
return answer, updated_history, None
except Exception as e: # noqa: BLE001
traceback.print_exc()
return f"Error: {e!s}", conversation_history, None
def answer_question_stream_api(
image: Image.Image,
question: str,
conversation_history: list[dict[str, Any]],
current_image_path: str | None,
) -> Generator[str, None, None]:
"""Stream an answer token-by-token via the remote API.
Drop-in replacement for ``infer_vision_qa.answer_question_stream``.
"""
try:
image = image.convert("RGB")
if not conversation_history:
new_user_turn: dict[str, Any] = {"role": "user", "content": [
{"type": "image"},
{"type": "text", "text": question},
]}
else:
new_user_turn = {"role": "user", "content": [
{"type": "text", "text": question},
]}
conversation = [*conversation_history, new_user_turn]
api_messages = _translate_messages(conversation, image)
yield from _call_chat_api_stream(api_messages)
except Exception as e: # noqa: BLE001
traceback.print_exc()
yield f"Error: {e!s}"
def extract_csv_stream_api(image: Image.Image) -> Generator[str, None, None]:
"""Stream CSV extraction token-by-token via the remote API.
Drop-in replacement for ``infer_chart2csv.extract_csv_stream``.
"""
try:
image = image.convert("RGB")
conversation = [{"role": "user", "content": [
{"type": "image"},
{"type": "text", "text": "<chart2csv>"},
]}]
api_messages = _translate_messages(conversation, image)
yield from _call_chat_api_stream(api_messages)
except Exception as e: # noqa: BLE001
traceback.print_exc()
yield f"Error: {e!s}"
def extract_csv_api(image: Image.Image) -> str:
"""Extract CSV data from a chart image via the remote API.
Drop-in replacement for ``infer_chart2csv.extract_csv``.
"""
try:
image = image.convert("RGB")
conversation = [{"role": "user", "content": [
{"type": "image"},
{"type": "text", "text": "<chart2csv>"},
]}]
api_messages = _translate_messages(conversation, image)
return _call_chat_api(api_messages)
except Exception as e: # noqa: BLE001
traceback.print_exc()
return f"Error: {e!s}"
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